Processing and analyzing huge incoming data is essential for supply chain management. Conventional systems initially load data acquired from different sources into the database. During this process the data is cleaned which involves validating (null columns check, specific data type check and so on) and checking for duplicate records. Once the cleansed data has been loaded, then ETL (extraction, transformation and load) operation are performed to calculate cubes or aggregate tables for business metrics used for real-time business analytics. This two tier approach takes lot of time to process the data